Energy-Efficient LDPC Decoder using DVFS for binary sources
This paper deals with reduction of the transmission power usage in the wireless sensor networks. A system with FEC can provide an objective reliability using less power than a system without FEC. We propose to study LDPC codes to provide reliable communication while saving power in the sensor networks. As shown later, LDPC codes are more energy efficient than those that use BCH codes. Another method to reduce the transmission cost is to compress the correlated data among a number of sensor nodes before transmission. A suitable source encoder that removes the redundant information bits can save the transmission power. Such a system requires distributed source coding. We propose to apply LDPC codes for both distributed source coding and source-channel coding to obtain a two-fold energy savings. Source and channel coding with LDPC for two correlated nodes under AWGN channel is implemented in this paper. In this iterative decoding algorithm is used for decoding the data, and it’s efficiency is compared with the new decoding algorithm called layered decoding algorithm which based on offset min sum algorithm. The usage of layered decoding algorithm and Adaptive LDPC decoding for AWGN channel reduces the decoding complexity and its number of iterations. So the power will be saved, and it can be implemented in hardware.